Smartphone Video Research Articles

Functional Syncope in Children and Adolescents: A Retrospective Cohort Study

BackgroundFunctional syncope, or psychogenic pseudosyncope, is often under-recognized. We aimed to show that functional syncope may be diagnosed in most pediatric patients by the initial neurological consultation. MethodsWe reviewed the medical records of patients who were evaluated from 2006 to 2022 in clinic for apparent transient loss of consciousness (a-TLOC) and probable functional syncope. Inclusion criteria included the following: (1) one or more episodes of a-TLOC; (2) spontaneous recovery; (3) age <19 years; (4) patients collapse or lie immobile andunresponsive to verbal stimulation; (5) normal or mildly increased heart rate and blood pressure, if assessed; (6) no other medical causes; and (7) episodes occurred during tilt, electroencephalography, or electrocardiogram or were seen by the author on a smartphone video or in clinic. Patients meeting criteria 1 to 7 were classified as “definite” functional syncope and those meeting criteria 1 to 6 as “probable” functional syncope. ResultsWe identified 31 patients with a-TLOC: 26 (23 females) had functional syncope, aged six to 17 years, whereas five were excluded (two functional seizures, one temporal lobe epilepsy, one vasovagal syncope, and one asthma). The clinical features of 13 patients in each group (definite versus probable) were not different statistically. Episodes were prolonged (1 to 270 minutes, mean 58 minutes) and frequent (daily or weekly in 65%), with eyes closed in 71% and eye flutter in 27%. After mean follow-up of 15 months in 14 patients: episodes disappeared in 29%, decreased >50% in 36%, and remained the same in 36%. ConclusionsFunctional syncope can be diagnosed at the initial neurological consultation without additional diagnostic testing in most patients.

A low-cost method for quantifying bouncing ball dynamics with smartphone video

Abstract This study employed a low-cost method for quantifying bouncing ball dynamics with smartphone video. High-speed video analysis was used to investigate the bouncing behaviour of different balls, including table tennis, rubber, and tennis balls, on a table tennis surface. To examine the effect of surface material on bouncing dynamics, the table tennis ball was also tested on wood and tile surfaces. Key parameters analysed included bounce height decay, the coefficient of restitution (COR), and the bounce half-life. Additionally, we measured the total bouncing time and analysed the relationship between changes in gravitational potential energy, kinetic energy, and total mechanical energy (ME). Our results revealed a significant correlation between the COR and the decay rate of bounce height. Balls with higher COR values, indicative of lower energy loss per bounce, exhibited slower decay rates, resulting in longer bounce half-lives and extended total bounce times. For instance, the table tennis ball on a tile surface demonstrated a high COR of 0.93, a bounce half-life of 4.65 bounces, and a total bounce time of 8.22 ± 0.34 s. This suggests that material properties such as stiffness and elasticity of both the ball and the surface significantly influence the COR and decay rate, beyond just surface smoothness. Furthermore, our analysis of ME changes in the bouncing balls aligns with theoretical predictions, providing insights into the energy transformations occurring during bouncing. This improved understanding can also be a valuable tool for educators, helping teachers and students bridge the gap between theory and real-world observations, leading to a deeper grasp of the concepts.

No Consistent Evidence for Associations Between Various Forms of Social Media Usage and Emotional Prowess: A Multi-⁠Study Approach With Three Adult Samples

The good and bad impacts of social media on individuals and societies remain poorly understood and highly debated. An often-discussed, yet little-studied worry about social media usage is that it may breed diminished social and emotional abilities. Here, we tested this assumption across three studies with adult samples (N = 316, 1,879, 903). We used different indicators of emotional prowess (i.e., emotional intelligence, emotion recognition), a broad set of social media usage measures and adopted a three-pronged analysis approach featuring zero-order correlations, multiple regressions, and conditional random forests. Our findings do not support consistent evidence for associations between social media usage and emotional prowess. Instead, we find conflicting evidence for passive social media usage (related to lower overall emotional intelligence but better emotion recognition) and active social media usage (related to higher overall emotional intelligence but worse emotion recognition). We find some evidence for positive associations between emotional prowess and general smartphone usage and text messaging usage. Further, we find largely inconsistent and/or null effects for social media addiction, general social media usage, general smartphone usage, video gaming, and media sharing. In the absence of consistent effects of social media usage, we find strong, robust, and replicable associations between age and emotional prowess.

Smartphone video imaging: A versatile, low-cost technology for food authentication

This study presents a low-cost smartphone-based imaging technique called smartphone video imaging (SVI) to capture short videos of samples that are illuminated by a colour-changing screen. Assisted by artificial intelligence, the study develops new capabilities to make SVI a versatile imaging technique such as the hyperspectral imaging (HSI). SVI enables classification of samples with heterogeneous contents, spatial representation of analyte contents and reconstruction of hyperspectral images from videos. When integrated with a residual neural network, SVI outperforms traditional computer vision methods for ginseng classification. Moreover, the technique effectively maps the spatial distribution of saffron purity in powder mixtures with predictive performance that is comparable to that of HSI. In addition, SVI combined with the U-Net deep learning module can produce high-quality images that closely resemble the target images acquired by HSI. These results suggest that SVI can serve as a consumer-oriented solution for food authentication.

Automated analysis of spontaneous eye blinking in patients with acute facial palsy or facial synkinesis

Although patients with facial palsy often complain of disturbed eye blinking which may lead to visual impairment, a blinking analysis is not part of routine grading of facial palsy. Twenty minutes of spontaneous eye blinking at rest of 30 patients with facial palsy (6 with acute palsy; 24 patients with facial synkinesis; median age: 58 years, 67% female), and 30 matched healthy probands (median age: 57 years; 67% female) was smart phone video recorded. A custom computer program automatically extracted eye measures and determined the eye closure rate (eye aspect ratio [EAR]), blink frequency, and blink duration. Facial Clinimetric Evaluation (FaCE), Facial Disability Index (FDI) were assessed as patient-reported outcome measures. The minimal EAR, i.e., minimal visible eye surface during blinking, was significantly higher on the paretic side in patients with acute facial palsy than in patients with synkinesis or in healthy controls. The blinking frequency on the affected side was significantly lower in both patient groups compared to healthy controls. Vice versa, blink duration was longer in both patient groups. There was no clear correlation between the blinking values and FaCE and FDI. Blinking parameters are easy to estimate automatically and add a functionally important parameter to facial grading.

Smartphones and video as security articulation infrastructures: evidencing Black Lives Matter

Abstract Smartphone videos can co-constitute security reality. As smartphones spread in the 2010s, videos of deadly police violence against Black United States citizens became common, and over time these videos co-constituted anti-Black police violence as a security issue, which found its expression as Black Lives Matter (BLM). This article questions the role that smartphones and video play for BLM, and argues that security theory needs a better grasp of security articulation. Mapping the mediation of BLM's first decade, the article documents that smartphones are security articulation infrastructures as bystanders routinely rely on smartphone video to articulate security. The epistemic authority of video enables BLM videos to act as infrastructural gateways connecting established mass media to new vernacular media. Video mediation denies recognized figures of authority interpretive monopoly and enables non-elites to participate in constituting security reality, creating a room for non-elite Black Americans' articulation of insecurity. The article shows that still images and videos are different in this respect, and calls for security theory to take articulation formats and infrastructures seriously. When leaving ‘communication’ to other disciplines or enacting government responses as constitutive of (visual) security, scholarship risks overlooking the epistemic racism limiting security articulation in ‘old’ mass media, and risks making security theory complicit in epistemically silencing the voices of common, marginalized and racialized people.

Smartphone Video Education-Based Diaphragmatic Respiratory Intervention As An Effort To Improve The Comfort Of Breast Cancer Patients Who Undergoing Chemotherapy At Arifin Achmad Hospital Riau Province

Chemotherapy drugs have a systemic effect that can kill cancer cells as well as healthy cells, causing discomfort to breast cancer patients due to the side effects of the treatment. One of the non-pharmacological treatments to reduce the symptoms of discomfort in breast cancer patients undergoing chemotherapy is diaphragmatic breathing which has benefits for mental and physical health. This study aims to determine the effect of diaphragmatic breathing intervention based on smartphone video education as an effort to increase the comfort of breast cancer patients undergoing chemotherapy. This research uses a Quasy Experiment With Pre-Test-Post-Test design. Diaphragmatic breathing exercise intervention was carried out for 10 minutes with a frequency of 3 times a day until day 7 after chemotherapy. Data were analyzed using the Wilxocon test. The research results in this study show the influence of diaphragmatic breathing exercises on the comfort of breast cancer patients undergoing chemotherapy. Conclusion: nurses are advised to educate breast cancer patients undergoing chemotherapy to carry out this intervention while at home.

Microsurgical Practice with Use of Smartphone Camera as the Microscopic Field.

Accessibility of microsurgical equipment is a major barrier to proper training of surgeons before live patient free flap surgery. A technique is presented that uses a smartphone camera as the microscopic field, eliminating the need for an expensive operative microscope for surgical practice. A convenient and cost-effective simulation protocol could reduce the time frame of the microsurgery learning curve. Furthermore, the use of the smartphone video function may allow improved feedback by mentors, improving access and communication between microsurgical teachers and learners. The PocketSuture smartphone stand is a commercially available device that allows the smartphone camera to be used as magnification. The proposed education protocol included suture practice, vessel dissection, and free tissue transfer in nonliving animal models, with vessel anastomosis and patency confirmation performed with a smartphone camera for field magnification. Video of the suturing technique allowed feedback from the mentor. A progressive suturing protocol leading to the ability to perform microsurgical anastomosis on nonliving animal models was developed. The basic costs for the stand, instrument set and suture were less than $500. The PocketSuture smartphone stand can be used for microsurgical training with real-time video for plastic surgery learners with limited access to microscopes and local mentors.

High-Altitude Precision Landing by Smartphone Video Guidance Sensor and Sensor Fusion

This paper describes the deployment, integration, and demonstration of the Smartphone Video Guidance Sensor (SVGS) as novel technology for autonomous 6-DOF proximity maneuvers and high-altitude precision landing of UAVs via sensor fusion. The proposed approach uses a vision-based photogrammetric position and attitude sensor (SVGS) to support the precise automated landing of a UAV from an initial altitude above 100 m to ground, guided by an array of landing beacons. SVGS information is fused with other on-board sensors at the flight control unit to estimate the UAV’s position and attitude during landing relative to a ground coordinate system defined by the landing beacons. While the SVGS can provide mm-level absolute positioning accuracy depending on range and beacon dimensions, the proper operation of the SVGS requires a line of sight between the camera and the beacon, and readings can be disturbed by environmental lighting conditions and reflections. SVGS readings can therefore be intermittent, and their update rate is not deterministic since the SVGS runs on an Android device. The sensor fusion of the SVGS with on-board sensors enables an accurate and reliable update of the position and attitude estimates during landing, providing improved performance compared to state-of-art automated landing technology based on an infrared beacon, but its implementation must address the challenges mentioned above. The proposed technique also shows significant advantages compared with state-of-the-art sensors for High-Altitude Landing, such as those based on LIDAR.

Effective evaluation of HGcnMLP method for markerless 3D pose estimation of musculoskeletal diseases patients based on smartphone monocular video.

Markerless pose estimation based on computer vision provides a simpler and cheaper alternative to human motion capture, with great potential for clinical diagnosis and remote rehabilitation assessment. Currently, the markerless 3D pose estimation is mainly based on multi-view technology, while the more promising single-view technology has defects such as low accuracy and reliability, which seriously limits clinical application. This study proposes a high-resolution graph convolutional multilayer perception (HGcnMLP) human 3D pose estimation framework for smartphone monocular videos and estimates 15 healthy adults and 12 patients with musculoskeletal disorders (sarcopenia and osteoarthritis) gait spatiotemporal, knee angle, and center-of-mass (COM) velocity parameters, etc., and compared with the VICON gold standard system. The results show that most of the calculated parameters have excellent reliability (VICON, ICC (2, k): 0.853-0.982; Phone, ICC (2, k): 0.839-0.975) and validity (Pearson r: 0.808-0.978, p0.05). In addition, the proposed system can better evaluate human gait balance ability, and the K-means++ clustering algorithm can successfully distinguish patients into different recovery level groups. This study verifies the potential of a single smartphone video for 3D human pose estimation for rehabilitation auxiliary diagnosis and balance level recognition, and is an effective attempt at the clinical application of emerging computer vision technology. In the future, it is hoped that the corresponding smartphone program will be developed to provide a low-cost, effective, and simple new tool for remote monitoring and rehabilitation assessment of patients.

Unexpected corneal reflection phenomenon alters smartphone 3D image-based models of the eye

Abstract Reconstruction of a 3D eye model by photogrammetry from a smartphone video could be prospectively used in self-diagnosis, screening and telemedicine monitoring of diseases of the front part of the eye and its surroundings. The main use could be found in the treatment of diseases of the curvature and surface of the cornea and in follow-up after some refractive procedures. In our work, we create 3D image-based models of the eye after scanning the face with a smartphone. An unexpected phenomenon appeared during the reconstruction of the transparent cornea – a crater-like depression was formed at the place where nearby objects reflected on the cornea, which corresponds to the first Purkinje image, the so-called glint. We thus encountered complications that may arise when modelling transparent living structures from a video taken in a normal environment, which will need to be solved if we want to create such 3D models of the eye using this method for medical purposes. Another 3D reconstruction approach or additional algorithms must be considered as a future work.

Algorithmic assessment of shoulder function using smartphone video capture and machine learning

Tears within the stabilizing muscles of the shoulder, known as the rotator cuff (RC), are the most common cause of shoulder pain—often presenting in older patients and requiring expensive advanced imaging for diagnosis. Despite the high prevalence of RC tears within the elderly population, there is no previously published work examining shoulder kinematics using markerless motion capture in the context of shoulder injury. Here we show that a simple string pulling behavior task, where subjects pull a string using hand-over-hand motions, provides a reliable readout of shoulder mobility across animals and humans. We find that both mice and humans with RC tears exhibit decreased movement amplitude, prolonged movement time, and quantitative changes in waveform shape during string pulling task performance. In rodents, we further note the degradation of low dimensional, temporally coordinated movements after injury. Furthermore, a logistic regression model built on our biomarker ensemble succeeds in classifying human patients as having a RC tear with > 90% accuracy. Our results demonstrate how a combined framework bridging animal models, motion capture, convolutional neural networks, and algorithmic assessment of movement quality enables future research into the development of smartphone-based, at-home diagnostic tests for shoulder injury.

Wellbeing, loneliness, health-related quality of life and perception of technology of older adults in Slovenian senior homes: a cross-sectional study

Background: Older adults can experience loneliness, low wellbeing, and poor health, while certain technologies could alleviate some of these issues. This paper presents findings from a study conducted in Slovenian senior homes, examining the wellbeing, loneliness, health-related quality of life, and perceptions of technology among older adults without significant cognitive issues. Methods: Older adults (n = 73) responded to questionnaires on wellbeing, loneliness, and health-related quality of life. They also provided their opinion on four different types of technology: a smartphone (SeniorsPhone) and television-based video calling system adapted to older adults (Daisy), a smartwatch (Fitbit), and an air quality sensor. Results: The results indicate that most examined older adults experience low or moderate levels of loneliness, and most are characterized by average or high levels of wellbeing. The participants also report no significant issues with self-care and accomplishing daily activities. However, more than half of the participants report experiencing some problems with pain/discomfort and mobility. Older adults generally trust evaluated technologies with their personal data, believe that the technologies provide reliable information, and perceive technologies as useful. Interestingly, older adults that reported higher levels of wellbeing and lower levels of loneliness tended to perceive the smartwatch as more usable. This suggests that at least for some technologies, the perception of usability depends on how people feel in general. Conclusions: Residents of Slovenian senior homes that do not have significant cognitive issues report relatively high wellbeing and health-related quality of life and low loneliness, together with positive perceptions of different technologies. These findings can be used to inform the development of age-appropriate technologies for senior home residents.

Rotating machinery speed extraction through smartphone video acquisition from a radial viewpoint

This article investigates the viability of using a smartphone as a cost-effective tool for rotational speed extraction. The proposed method exploits the geometrical image deformations induced by a smartphone’s rolling shutter camera, which reads pixel lines sequentially with a delay equal to the rolling shutter period. This characteristic period is the basis for the developed methodology and allows measuring constant and varying speeds above the Nyquist limit related to the camera’s frame rate. With respect to the rotating shaft, the smartphone is pointed to the side surface of the shaft (radial viewpoint). A method is proposed to measure the speed from the deformation of a zebra pattern as a consequence of the sequential readout of a rolling shutter camera. A mathematical model, which also takes into account a possible misalignment between the shaft and the camera’s rolling shutter reading direction, is developed and validated on an in-house test rig. It is shown that the proposed method is robust against changing lighting conditions and a misalignment between the shaft and the smartphone camera. Normalized Root-Mean-Square Errors (NRMSE) of about 3% (or less) are reached for the smartphone aligned with the shaft with peaks in the percentage error of about 5% to 8%. Nevertheless, even for a misalignment of 60°, the NRMSE is only 4% with variations in the percentage error to about 10%.The proposed method shows promising results with room for improvements, making it possible to develop a smartphone application to measure a shaft’s rotational speed in the future.

Low-rate smartphone videoscopy for microsecond luminescence lifetime imaging with machine learning.

Time-resolved techniques have been widely used in time-gated and luminescence lifetime imaging. However, traditional time-resolved systems require expensive lab equipment such as high-speed excitation sources and detectors or complicated mechanical choppers to achieve high repetition rates. Here, we present a cost-effective and miniaturized smartphone lifetime imaging system integrated with a pulsed ultraviolet (UV) light-emitting diode (LED) for 2D luminescence lifetime imaging using a videoscopy-based virtual chopper (V-chopper) mechanism combined with machine learning. The V-chopper method generates a series of time-delayed images between excitation pulses and smartphone gating so that the luminescence lifetime can be measured at each pixel using a relatively low acquisition frame rate (e.g. 30 frames per second [fps]) without the need for excitation synchronization. Europium (Eu) complex dyes with different luminescent lifetimes ranging from microseconds to seconds were used to demonstrate and evaluate the principle of V-chopper on a 3D-printed smartphone microscopy platform. A convolutional neural network (CNN) model was developed to automatically distinguish the gated images in different decay cycles with an accuracy of >99.5%. The current smartphone V-chopper system can detect lifetime down to ∼75 µs utilizing the default phase shift between the smartphone video rate and excitation pulses and in principle can detect much shorter lifetimes by accurately programming the time delay. This V-chopper methodology has eliminated the need for the expensive and complicated instruments used in traditional time-resolved detection and can greatly expand the applications of time-resolved lifetime technologies.

Smartphone video games improve cognitive function in patients with chronic schizophrenia: a randomized controlled trial.

This study aimed to examine the efficacy of video games in improving cognitive function in chronic patients with schizophrenia and to evaluate the biomarker of video games for cognitive function. The patients in the game group were requested to play single-player video games on their smartphones for 1h per day, five times a week for 6weeks. Those in the control group watched television for 1h per day, five times a week for 6weeks. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Stroop Color and Word Test (SCWT). Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS), Global Assessment of Functioning (GAF), General Self-Efficacy Scale (GSE), Problematic Mobile Gaming Questionnaire (PMGQ), and Patient Health Questionnaire-9 (PHQ-9). The game group demonstrated improved RBANS total score during the trial. There were no significant group effects among all SCWT scores. The game group demonstrated greater improvement on the PANSS Negative Scale, and global function (GAF score). The PMGQ scores were lower than the cutoff score at all time points in both groups. There were no significant group differences in the PHQ-9 and GSE scores. The serum BDNF levels were significantly higher in the game group following 6weeks of video game intervention. The BDNF serum levels of all participants were positively associated with the RBANS total scores. This preliminary study suggested that video games can improve cognitive function in schizophrenia patients. Serum BDNF levels may be a suitable biomarker for predicting an improvement in cognitive function in schizophrenia patients.Trial registration: This study was registered on March 11, 2021 (ChiCTR2100044113).Clinical trials: Smartphone video games improve cognitive function in patients with chronic schizophrenia; https://www.chictr.org.cn/hvshowproject.aspx?id=95623 ; ChiCTR2100044113.

Precision landing comparison between smartphone video guidance sensor and IRLock by hardware-in-the-loop emulation

The Smartphone Video Guidance Sensor (SVGS) is an emerging technology developed by NASA Marshall Space Flight Center that uses a vision-based approach to accurately estimate the six-state position and orientation vectors of an illuminated target of known dimensions with respect to a coordinate frame fixed to the camera. SVGS is a software-based sensor that can be deployed using a host platform’s resources (CPU and camera) for proximity operations and formation flight of drones or spacecraft. The SVGS output is calculated based on photogrammetric analysis of the light blobs in each image; its accuracy in linear and angular motion at different velocities has previously been successfully demonstrated [9]. SVGS has several potential applications in guidance, navigation, motion control, and proximity operations as a reduced-cost, compact, reliable option to competing technologies such as LiDAR or infrared sensing. One of the applications envisioned by NASA for SVGS is planetary/lunar autonomous landing. This paper aims to compare the SVGS performance in autonomous landing with existing technologies: a combination of infrared beacon technology (IRLock) and LiDAR. The comparison is based on a hardware-in-the-loop emulation of a precision landing experiment using a computer-controlled linear motion to emulate the approach motion and the ROS/Gazebo environment to emulate the response of the flight controller to the environment during landing. Results suggest that SVGS performs better than the existing IRLock with LiDAR sensor combination.

Slow-motion smartphone video improves interobserver reliability of gait assessment in ambulatory cerebral palsy.

Structured visual gait assessment is essential for the evaluation of pediatric patients with neuromuscular conditions. The purpose of this study was to evaluate the benefit of slow-motion video recorded on a standard smartphone to augment visual gait assessment. Coronal and sagittal plane videos of the gait of five pediatric subjects were recorded on a smartphone, including four subjects with ambulatory cerebral palsy and one subject without gait pathology. Twenty-one video scorers were recruited and randomized to evaluate slow-motion or normal-speed videos utilizing the Edinburgh Visual Gait Score. The slow-motion group (N = 11) evaluated the videos at one-eighth speed, and the normal-speed group (N = 10) evaluated the same videos at normal speed. Interrater reliabilities were determined by calculating intraclass correlation coefficients for each group as a whole, for each Edinburgh Visual Gait Score item, and after stratification by evaluator experience level. The slow-motion group exhibited an intraclass correlation coefficient of 0.65 (95% confidence interval: 0.58-0.73), whereas the normal-speed group exhibited an intraclass correlation coefficient of 0.57 (95% confidence interval: 0.49-0.65). For less-experienced scorers, intraclass correlation coefficients of 0.62 (95% confidence interval: 0.53-0.71) and 0.50 (95% confidence interval: 0.40-0.59) were calculated for slow motion and normal speed, respectively. For more-experienced scorers, intraclass correlation coefficients of 0.69 (95% confidence interval: 0.61-0.76) and 0.67 (95% confidence interval: 0.58-0.75) were calculated for slow motion and normal speed, respectively. Visual gait assessment is enhanced by the use of slow-motion smartphone video, a tool widely available throughout the world with no marginal cost. level I, randomized study.

Automated Implementation of the Edinburgh Visual Gait Score (EVGS) Using OpenPose and Handheld Smartphone Video

Recent advancements in computing and artificial intelligence (AI) make it possible to quantitatively evaluate human movement using digital video, thereby opening the possibility of more accessible gait analysis. The Edinburgh Visual Gait Score (EVGS) is an effective tool for observational gait analysis, but human scoring of videos can take over 20 min and requires experienced observers. This research developed an algorithmic implementation of the EVGS from handheld smartphone video to enable automatic scoring. Participant walking was video recorded at 60 Hz using a smartphone, and body keypoints were identified using the OpenPose BODY25 pose estimation model. An algorithm was developed to identify foot events and strides, and EVGS parameters were determined at relevant gait events. Stride detection was accurate within two to five frames. The level of agreement between the algorithmic and human reviewer EVGS results was strong for 14 of 17 parameters, and the algorithmic EVGS results were highly correlated (r &gt; 0.80, “r” represents the Pearson correlation coefficient) to the ground truth values for 8 of the 17 parameters. This approach could make gait analysis more accessible and cost-effective, particularly in areas without gait assessment expertise. These findings pave the way for future studies to explore the use of smartphone video and AI algorithms in remote gait analysis.

The Effect of Smartphone Video on Lead Time to Diagnosis of Infantile Spasms

To assess whether access to smartphone video capture of infantile spasms at initial presentation is associated with improved time to diagnosis and treatment. We conducted a collaborative retrospective cohort study of 80 consecutive infants with confirmed infantile epileptic spasms syndrome initially presenting from 2015 to 2021 at 2 US pediatric centers. Statistical methods used included Mann-Whitney U test to assess the difference in lead times to electroencephalogram (EEG), diagnosis, and treatment between groups with and without video capture. A χ2 analysis was used to assess differences in demographics, clinical characteristics, and treatment outcomes between groups. Multivariate regression analysis was used to account for etiology types and infantile spasms capture on EEG. Patients with smartphone video infantile spasms capture initially presented a median of 9days earlier (P=.02), had their first EEG 16days earlier (P=.007), and were diagnosed and started treatment 17days earlier (P=.006 and P=.008, respectively) compared with the nonvideo group. The video group had a 25% greater response to initial standard treatment (P=.02) and a 21% greater freedom from infantile spasms at long-term follow-up (P=.03), although this long-term outcome lost statistical significance after adjustment for etiology type (P=.07) and EEG capture of infantile spasms (P=.059). Our findings suggest a benefit of smartphone video capture of infantile spasms in reduced time to diagnosis and initial standard treatment, which are associated with improved treatment response rates. Substantial differences in lead times and treatment response highlight the clinical importance of pediatricians recommending caregivers to obtain smartphone video of events concerning for infantile spasms.